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丹麦人群中肥胖相关疾病的患病率——基于算法的筛查项目结果

Prevalence of Obesity-Related Disease in a Danish Population - The Results of an Algorithm-Based Screening Program.

作者信息

Juhl Claus B, Bladbjerg Else Marie, Gram Bibi, Knudsen Torben, Lauridsen Mette Munk, Nygaard Niels-Peter Brøchner, Drøjdahl Ryg Nina, Skadhauge Lars, Münster Anna-Marie Bloch

机构信息

Department of Endocrinology, University Hospital of Southern Denmark, Esbjerg, Denmark.

Steno Diabetes Center Odense, University Hospital of Southern Denmark, Odense, Denmark.

出版信息

Diabetes Metab Syndr Obes. 2024 Jun 19;17:2505-2517. doi: 10.2147/DMSO.S456028. eCollection 2024.

Abstract

PURPOSE

The prevalence of obesity continues to rise. People with obesity are at increased risk of several diseases. We tested an algorithm-based screening program for people with a BMI above 30 kg/m and present data on the prevalence of previously undiagnosed obesity-related diseases.

PATIENTS AND METHODS

Seven hundred and sixty-nine persons with BMI > 30 kg/m and age 18-60 years were screened for diabetes (assessed by glycosylated hemoglobin and oral glucose tolerance test at HbA1c 43-48 mmol/mol), sleep apnea (screened by questionnaires and assessed by cardiorespiratory monitoring at indication of sleep disorder), liver steatosis or liver fibrosis (assessed by biochemistry and fibroscan) and arterial hypertension (assessed by both office and 24-hour blood pressure measurement). A reference group of people with a BMI of 18.5-29.9 kg/m was established.

RESULTS

Of those referred, 73.0% were women. We identified new diabetes in 4.2%, prediabetes in 9.1%, moderate-to-severe sleep apnea in 25.1%, increased liver fat and increased liver stiffness in 68.1% and 17.4%, respectively, and hypertension or masked hypertension in 19.0%. The prevalence of diseases was much higher among men and increased with BMI. Except for hypertension, we found few participants with undiagnosed disease in the reference group.

CONCLUSION

An algorithm-based screening program is feasible and reveals undiagnosed obesity-related disease in a large proportion of the participants. The disproportional referral pattern calls for a tailored approach aiming to include more men with obesity.

TRIAL REGISTRATION

Inclusion of the non-obese group was approved by the Scientific Ethics Committee of The Region of Southern Denmark (project identification number: S-20210091), and the study was reported at clinicaltrials.gov (NCT05176132).

摘要

目的

肥胖症的患病率持续上升。肥胖人群患多种疾病的风险增加。我们对体重指数(BMI)高于30kg/m²的人群测试了一种基于算法的筛查程序,并呈现了此前未诊断出的肥胖相关疾病的患病率数据。

患者与方法

对769名BMI>30kg/m²且年龄在18至60岁之间的人进行了糖尿病筛查(通过糖化血红蛋白和糖化血红蛋白水平为43 - 48mmol/mol时的口服葡萄糖耐量试验进行评估)、睡眠呼吸暂停筛查(通过问卷筛查,并在有睡眠障碍指征时通过心肺监测进行评估)、肝脂肪变性或肝纤维化评估(通过生化检查和肝脏弹性成像进行评估)以及动脉高血压评估(通过诊室血压测量和24小时血压测量进行评估)。设立了一个BMI为18.5 - 29.9kg/m²的参考人群组。

结果

在被转诊的人群中,73.0%为女性。我们发现新发糖尿病的比例为4.2%,糖尿病前期为9.1%,中度至重度睡眠呼吸暂停为25.1%,肝脏脂肪增加和肝脏硬度增加的比例分别为68.1%和17.4%,高血压或隐匿性高血压为19.0%。疾病的患病率在男性中要高得多,且随BMI增加而升高。除高血压外,我们在参考人群组中发现很少有未诊断出疾病的参与者。

结论

基于算法的筛查程序是可行的,并且在很大一部分参与者中发现了未诊断出的肥胖相关疾病。不均衡的转诊模式要求采取一种针对性的方法,旨在纳入更多肥胖男性。

试验注册

纳入非肥胖组已获得丹麦南部地区科学伦理委员会的批准(项目识别号:S - 20210091),该研究已在clinicaltrials.gov上报告(NCT05176132)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0991/11193984/1dbb40d69e0d/DMSO-17-2505-g0001.jpg

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